CALGB50303-Tumor-Annotations | Annotations for Rituximab and Combination Chemotherapy in Treating Patients With Diffuse Large B-Cell Non-Hodgkin's Lymphoma
DOI: 10.7937/9JER-G980 | Data Citation Required | Analysis Result
Location | Subjects | Size | Updated | |||
---|---|---|---|---|---|---|
Lymphoma | Various | 155 | Tumor segmentations, Seed points | 2023/03/30 |
Summary
This dataset contains image annotations derived from the NCI Clinical Trial “Rituximab and Combination Chemotherapy in Treating Patients With Diffuse Large B-Cell Non-Hodgkin’s Lymphoma (CALGB50303)”. This dataset was generated as part of an NCI project to augment TCIA datasets with annotations that will improve their value for cancer researchers and AI developers. For each patient, every DICOM Study and DICOM Series was reviewed to identify and annotate the clinically relevant time points and sequences. In a typical patient all available time points were annotated. In a typical patient the following annotation rules were followed: a. PERCIST criteria was followed. Specifically, the lesions estimated to have the most elevated SUVmax were annotated. At each time point:Annotation Protocol
b. Lesions were annotated in the axial plane. If no axial plane were available, lesions were annotated in the coronal plane.
c. Lesions were annotated on the attenuation corrected PET series as well as the diagnostic contrast-enhanced CT. If no diagnostic contrast-enhanced CT was available for that timepoint, then the non-contrast CT portion of the PET/CT was annotated.
d. A maximum of 5 lesions were annotated per patient scan (timepoint); no more than 2 per organ. For the purposes of this project, the lymph nodes constitute 1 organ, while other lymphatic structures such as the spleen, salivary glands, and Waldeyer’s ring structures constitute separate organs. The same 5 lesions were annotated at each time point. RECIST 1.1 principles were followed. Specifically, lymph nodes were annotated if > 1.5 cm in short axis. Other lesions were annotated if > 1 cm.
e. Lesions were labeled separately.
f. Seed points were automatically generated and reviewed by a radiologist.
Important supplementary information and sample code
Data Access
Version 1: Updated 2023/03/30
Title | Data Type | Format | Access Points | Subjects | License | |||
---|---|---|---|---|---|---|---|---|
CALGB50303 Annotations - Segmentations, Seed Points, and Negative Findings Assessments | RTSTRUCT | DICOM | Download requires NBIA Data Retriever |
155 | 519 | 3,077 | 3,077 | NCTN/NCORP Data Archive License (Without Collaborative Agreement) |
CALGB50303 Annotation Metadata | Classification, Measurement | CSV | CC BY 4.0 |
Collections Used In This Analysis Result
Title | Data Type | Format | Access Points | Subjects | License | |||
---|---|---|---|---|---|---|---|---|
Original CALGB50303 Images used to create Segmentations and Seed Points | CT, PT | DICOM | Requires NBIA Data Retriever |
152 | 448 | 661 | 204,738 | NCTN/NCORP Data Archive License (Without Collaborative Agreement) |
Original CALGB50303 Images used to create Negative Assessment reports | CT, PT | DICOM | Requires NBIA Data Retriever |
89 | 183 | 209 | 59,572 | NCTN/NCORP Data Archive License (Without Collaborative Agreement) |
Additional Resources For This Dataset
- NCTN/NCORP Data Archive provides the Clinical Data files related to these subjects, and is also where you go to request access to the entire dataset
- Jupyter notebook demonstrating how to use the NBIA Data Retriever Command-Line Interface application and REST API (with authentication) to access these data
- Instructions for Visualizing these data in 3D Slicer
Citations & Data Usage Policy
Data Citation Required: Users must abide by the TCIA Data Usage Policy and Restrictions. Attribution must include the following citation, including the Digital Object Identifier:
Data Citation |
|
Rozenfeld, M., & Jordan, P. (2023). Annotations for Rituximab and Combination Chemotherapy in Treating Patients With Diffuse Large B-Cell Non-Hodgkin’s Lymphoma (CALGB50303-Tumor-Annotations) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/9JER-G980 |
Related Publications
Publications by the Dataset Authors
The authors recommended the following as the best source of additional information about this dataset:
Research Community Publications
TCIA maintains a list of publications that leveraged this dataset. If you have a manuscript you’d like to add please contact TCIA’s Helpdesk.